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Riccardo Rosati - One of the best experts on this subject based on the ideXlab platform.
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data complexity of query answering in description logics extended abstract
International Joint Conference on Artificial Intelligence, 2015Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We study the data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOrewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology.
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kyrie2 query rewriting under extensional constraints in elhio
International Semantic Web Conference, 2014Co-Authors: Jose Mora, Riccardo Rosati, Oscar CorchoAbstract:In this paper we study query answering and rewriting in ontologybased data access. Specifically, we present an algorithm for computing a perfect rewriting of unions of conjunctive queries posed over ontologies expressed in the description logic ELHIO, which covers the OWL 2 QL and OWL 2 EL profiles. The novelty of our algorithm is the use of a set of ABox dependencies, which are compiled into a so-called EBox, to limit the expansion of the rewriting. So far, EBoxes have only been used in query rewriting in the case of DL-Lite, which is less expressive than ELHIO. We have extensively evaluated our new query rewriting technique, and in this paper we discuss the tradeoff between the reduction of the size of the rewriting and the computational cost of our approach.
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data complexity of query answering in description logics
Artificial Intelligence, 2013Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:In this paper we study data complexity of answering conjunctive queries over description logic (DL) knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOL-rewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. FOL-rewritability means that query answering can be reduced to evaluating queries over the database corresponding to the ABox. Since first-order queries can be expressed in SQL, the importance of FOL-rewritability is that, when query answering enjoys this property, we can take advantage of Relational Data Base Management System (RDBMS) techniques for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. What emerges from our complexity analysis is that the description logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology. In this sense, they are the first description logics specifically tailored for effective query answering over very large ABoxes.
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on instance level update and erasure in description logic ontologies
Journal of Logic and Computation, 2009Co-Authors: Giuseppe De Giacomo, Maurizio Lenzerini, Antonella Poggi, Riccardo RosatiAbstract:A Description Logic (DL) ontology is constituted by two components, a TBox that expresses general knowledge about the concepts and their relationships, and an ABox that describes the properties of individuals that are instances of concepts. We address the problem of how to deal with changes to a DL ontology, when these changes affect only the ABox, i.e. when the TBox is considered invariant. We consider two basic changes, namely instance-level update and instance-level erasure, roughly corresponding to the addition and the deletion of a set of facts involving individuals. We characterize the semantics of instance-level update and erasure on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. Interestingly, DLs are typically not closed with respect to instance-level update and erasure, in the sense that the set of models corresponding to the application of any of these operations to a knowledge base in a DL L may not be expressible by ABoxes in L. In particular, we show that this is true for DL-LiteF, a tractable DL that is oriented towards data-intensive applications. To deal with this problem, we first introduce DL-LiteFS, a DL that minimally extends DL-LiteF and is closed with respect to instance-level update, and present a polynomial algorithm for computing instance-level update in this logic. Then, we provide a principled notion of best approximation with respect to a fixed language L of instance-level update and erasure, and exploit the algorithm for instance-level update for DL-LiteFS to get polynomial algorithms for approximated instance-level update and erasure for DL-LiteF. These results confirm the nice computational properties of DL-LiteF for data intensive applications, even where information about instances is not only read, but also written.
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tractable reasoning and efficient query answering in description logics the dl lite family
Journal of Automated Reasoning, 2007Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial-time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current database management systems. Since even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances.
Giuseppe De Giacomo - One of the best experts on this subject based on the ideXlab platform.
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data complexity of query answering in description logics extended abstract
International Joint Conference on Artificial Intelligence, 2015Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We study the data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOrewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology.
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data complexity of query answering in description logics
Artificial Intelligence, 2013Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:In this paper we study data complexity of answering conjunctive queries over description logic (DL) knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOL-rewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. FOL-rewritability means that query answering can be reduced to evaluating queries over the database corresponding to the ABox. Since first-order queries can be expressed in SQL, the importance of FOL-rewritability is that, when query answering enjoys this property, we can take advantage of Relational Data Base Management System (RDBMS) techniques for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. What emerges from our complexity analysis is that the description logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology. In this sense, they are the first description logics specifically tailored for effective query answering over very large ABoxes.
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on instance level update and erasure in description logic ontologies
Journal of Logic and Computation, 2009Co-Authors: Giuseppe De Giacomo, Maurizio Lenzerini, Antonella Poggi, Riccardo RosatiAbstract:A Description Logic (DL) ontology is constituted by two components, a TBox that expresses general knowledge about the concepts and their relationships, and an ABox that describes the properties of individuals that are instances of concepts. We address the problem of how to deal with changes to a DL ontology, when these changes affect only the ABox, i.e. when the TBox is considered invariant. We consider two basic changes, namely instance-level update and instance-level erasure, roughly corresponding to the addition and the deletion of a set of facts involving individuals. We characterize the semantics of instance-level update and erasure on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. Interestingly, DLs are typically not closed with respect to instance-level update and erasure, in the sense that the set of models corresponding to the application of any of these operations to a knowledge base in a DL L may not be expressible by ABoxes in L. In particular, we show that this is true for DL-LiteF, a tractable DL that is oriented towards data-intensive applications. To deal with this problem, we first introduce DL-LiteFS, a DL that minimally extends DL-LiteF and is closed with respect to instance-level update, and present a polynomial algorithm for computing instance-level update in this logic. Then, we provide a principled notion of best approximation with respect to a fixed language L of instance-level update and erasure, and exploit the algorithm for instance-level update for DL-LiteFS to get polynomial algorithms for approximated instance-level update and erasure for DL-LiteF. These results confirm the nice computational properties of DL-LiteF for data intensive applications, even where information about instances is not only read, but also written.
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tractable reasoning and efficient query answering in description logics the dl lite family
Journal of Automated Reasoning, 2007Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial-time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current database management systems. Since even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances.
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on the approximation of instance level update and erasure in description logics
National Conference on Artificial Intelligence, 2007Co-Authors: Giuseppe De Giacomo, Maurizio Lenzerini, Antonella Poggi, Riccardo RosatiAbstract:A Description Logics knowledge base is constituted by two components, called TBox and ABox, where the former expresses general knowledge about the concepts and their relationships, and the latter describes the properties of instances of concepts. We address the problem of how to deal with changes to a Description Logic knowledge base, when these changes affect only its ABox. We consider two types of changes namely update and erasure, and we characterize the semantics of these operations on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. It is well known that, in general, Description Logics are not closed with respect to updates, in the sense that the set of models corresponding to an update applied to a knowledge base in a Description Logic L may not be expressible by ABoxes in L. We show that this is true also for erasure. To deal with this problem, we introduce the notion of best approximation of an update (erasure) in a DL L, with the goal of characterizing the L ABoxes that capture the update (erasure) at best. We then focus on DL-LiteF, a tractable Description Logic, and present polynomial algorithms for computing the best approximation of updates and erasures in this logic, which shows that the nice computational properties of DL-LiteF are retained in dealing with the evolution of the ABox.
Maurizio Lenzerini - One of the best experts on this subject based on the ideXlab platform.
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data complexity of query answering in description logics extended abstract
International Joint Conference on Artificial Intelligence, 2015Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We study the data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOrewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology.
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data complexity of query answering in description logics
Artificial Intelligence, 2013Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:In this paper we study data complexity of answering conjunctive queries over description logic (DL) knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOL-rewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. FOL-rewritability means that query answering can be reduced to evaluating queries over the database corresponding to the ABox. Since first-order queries can be expressed in SQL, the importance of FOL-rewritability is that, when query answering enjoys this property, we can take advantage of Relational Data Base Management System (RDBMS) techniques for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. What emerges from our complexity analysis is that the description logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology. In this sense, they are the first description logics specifically tailored for effective query answering over very large ABoxes.
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on instance level update and erasure in description logic ontologies
Journal of Logic and Computation, 2009Co-Authors: Giuseppe De Giacomo, Maurizio Lenzerini, Antonella Poggi, Riccardo RosatiAbstract:A Description Logic (DL) ontology is constituted by two components, a TBox that expresses general knowledge about the concepts and their relationships, and an ABox that describes the properties of individuals that are instances of concepts. We address the problem of how to deal with changes to a DL ontology, when these changes affect only the ABox, i.e. when the TBox is considered invariant. We consider two basic changes, namely instance-level update and instance-level erasure, roughly corresponding to the addition and the deletion of a set of facts involving individuals. We characterize the semantics of instance-level update and erasure on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. Interestingly, DLs are typically not closed with respect to instance-level update and erasure, in the sense that the set of models corresponding to the application of any of these operations to a knowledge base in a DL L may not be expressible by ABoxes in L. In particular, we show that this is true for DL-LiteF, a tractable DL that is oriented towards data-intensive applications. To deal with this problem, we first introduce DL-LiteFS, a DL that minimally extends DL-LiteF and is closed with respect to instance-level update, and present a polynomial algorithm for computing instance-level update in this logic. Then, we provide a principled notion of best approximation with respect to a fixed language L of instance-level update and erasure, and exploit the algorithm for instance-level update for DL-LiteFS to get polynomial algorithms for approximated instance-level update and erasure for DL-LiteF. These results confirm the nice computational properties of DL-LiteF for data intensive applications, even where information about instances is not only read, but also written.
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tractable reasoning and efficient query answering in description logics the dl lite family
Journal of Automated Reasoning, 2007Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We propose a new family of description logics (DLs), called DL-Lite, specifically tailored to capture basic ontology languages, while keeping low complexity of reasoning. Reasoning here means not only computing subsumption between concepts and checking satisfiability of the whole knowledge base, but also answering complex queries (in particular, unions of conjunctive queries) over the instance level (ABox) of the DL knowledge base. We show that, for the DLs of the DL-Lite family, the usual DL reasoning tasks are polynomial in the size of the TBox, and query answering is LogSpace in the size of the ABox (i.e., in data complexity). To the best of our knowledge, this is the first result of polynomial-time data complexity for query answering over DL knowledge bases. Notably our logics allow for a separation between TBox and ABox reasoning during query evaluation: the part of the process requiring TBox reasoning is independent of the ABox, and the part of the process requiring access to the ABox can be carried out by an SQL engine, thus taking advantage of the query optimization strategies provided by current database management systems. Since even slight extensions to the logics of the DL-Lite family make query answering at least NLogSpace in data complexity, thus ruling out the possibility of using on-the-shelf relational technology for query processing, we can conclude that the logics of the DL-Lite family are the maximal DLs supporting efficient query answering over large amounts of instances.
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on the approximation of instance level update and erasure in description logics
National Conference on Artificial Intelligence, 2007Co-Authors: Giuseppe De Giacomo, Maurizio Lenzerini, Antonella Poggi, Riccardo RosatiAbstract:A Description Logics knowledge base is constituted by two components, called TBox and ABox, where the former expresses general knowledge about the concepts and their relationships, and the latter describes the properties of instances of concepts. We address the problem of how to deal with changes to a Description Logic knowledge base, when these changes affect only its ABox. We consider two types of changes namely update and erasure, and we characterize the semantics of these operations on the basis of the approaches proposed by Winslett and by Katsuno and Mendelzon. It is well known that, in general, Description Logics are not closed with respect to updates, in the sense that the set of models corresponding to an update applied to a knowledge base in a Description Logic L may not be expressible by ABoxes in L. We show that this is true also for erasure. To deal with this problem, we introduce the notion of best approximation of an update (erasure) in a DL L, with the goal of characterizing the L ABoxes that capture the update (erasure) at best. We then focus on DL-LiteF, a tractable Description Logic, and present polynomial algorithms for computing the best approximation of updates and erasures in this logic, which shows that the nice computational properties of DL-LiteF are retained in dealing with the evolution of the ABox.
Yaoxia Yang - One of the best experts on this subject based on the ideXlab platform.
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a simple and efficient oxidation system for the oxidation of alcohols utilizing oxone as oxidant catalyzed by polymer supported 2 iodobenzamide
Catalysis Letters, 2007Co-Authors: Ziqiang Lei, Penghua Yan, Yaoxia YangAbstract:\(\begin{array}{l}{\hbox{R}^1\hbox{R}^2\hbox{CHOH}} \\ {\hbox{RCH}_2\hbox{OH} }\end{array} \dynrightarrow{Oxone}{\hbox{CH}_3\hbox{CN/H}_2\hbox{O}, 70^{\circ}\hbox{C}} \begin{array}{l}{\hbox{R}^1\hbox{R}^2\hbox{CO}} \\ {\hbox{RCOOH}} \end{array}\) A simple and environmentally friendly procedure for the oxidation of alcohols is presented utilizing Oxone® (2KHSO5 · KHSO4 · K2 SO4) as oxidant and polymer-supported 2-iodobenzamide as catalyst in CH3CN/H2O mixed solvents.
Diego Calvanese - One of the best experts on this subject based on the ideXlab platform.
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handling inconsistencies due to class disjointness in sparql updates
International Semantic Web Conference, 2016Co-Authors: Albin Ahmeti, Diego Calvanese, Axel Polleres, Vadim SavenkovAbstract:The problem of updating ontologies has received increased attention in recent years. In the approaches proposed so far, either the update language is restricted to sets of ground atoms or, where the full SPARQL update language is allowed, the TBox language is restricted so that no inconsistencies can arise. In this paper we discuss directions to overcome these limitations. Starting from a DL-Lite fragment covering RDFS and concept disjointness axioms, we define three semantics for SPARQL instance-level ABox update: under cautious semantics, inconsistencies are resolved by rejecting updates potentially introducing conflicts; under brave semantics, instead, conflicts are overridden in favor of new information where possible; finally, the fainthearted semantics is a compromise between the former two approaches, designed to accommodate as much of the new information as possible, as long as consistency with the prior knowledge is not violated. We show how these semantics can be implemented in SPARQL via rewritings of polynomial size and draw first conclusions from their practical evaluation.
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data complexity of query answering in description logics extended abstract
International Joint Conference on Artificial Intelligence, 2015Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:We study the data complexity of answering conjunctive queries over Description Logic knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOrewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. What emerges from our complexity analysis is that the Description Logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology.
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data complexity of query answering in description logics
Artificial Intelligence, 2013Co-Authors: Diego Calvanese, Giuseppe De Giacomo, Maurizio Lenzerini, Domenico Lembo, Riccardo RosatiAbstract:In this paper we study data complexity of answering conjunctive queries over description logic (DL) knowledge bases constituted by a TBox and an ABox. In particular, we are interested in characterizing the FOL-rewritability and the polynomial tractability boundaries of conjunctive query answering, depending on the expressive power of the DL used to express the knowledge base. FOL-rewritability means that query answering can be reduced to evaluating queries over the database corresponding to the ABox. Since first-order queries can be expressed in SQL, the importance of FOL-rewritability is that, when query answering enjoys this property, we can take advantage of Relational Data Base Management System (RDBMS) techniques for both representing data, i.e., ABox assertions, and answering queries via reformulation into SQL. What emerges from our complexity analysis is that the description logics of the DL-Lite family are essentially the maximal logics allowing for conjunctive query answering through standard database technology. In this sense, they are the first description logics specifically tailored for effective query answering over very large ABoxes.
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the complexity of conjunctive query abduction in dl lite
Description Logics, 2011Co-Authors: Diego Calvanese, Magdalena Ortiz, Mantas Simkus, Giorgio StefanoniAbstract:In order to meet usability requirements, most logic-based applications provide explanation facilities for reasoning services. This holds also for DLs, where research focused on the explanation of both TBox reasoning and, more recently, query answering. Besides explaining the presence of a tuple in a query answer, it is important to explain also why a given tuple is missing. We address this latter problem for (conjunctive) query answering over DL-Lite ontologies, by adopting abductive reasoning, that is, we look for additions to the ABox that force a given tuple to be in the result. As reasoning tasks, we consider existence and recognition of an explanation, and relevance and necessity of a certain assertion for an explanation. We characterize the computational complexity of these problems for subset minimal and cardinality minimal solutions.
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verification of conjunctive query based semantic artifacts
International Workshop Description Logics, 2011Co-Authors: Babak Bagheri Hariri, Diego Calvanese, Riccardo De MasellisAbstract:We introduce semantic artifacts, which are a mechanism that provides both a semantically rich representation of the information on the domain of interest in terms of an ontology, including the underlying data, and a set of actions to change such information over time. In this paper, the ontology is specified as a DL-Lite TBox together with an ABox that may contain both (known) constants and unknown individuals (labeled nulls, represented as Skolem terms). Actions are specified as sets of conditional effects, where conditions are based on conjunctive queries over the ontology (TBox and ABox), and effects are expressed in terms of new ABoxes. In this setting, which is obviously not finite state, we address the verification of temporal/dynamic properties expressed in μ-calculus. Notably, we show decidability of verification, under a suitable restriction inspired by the notion of acyclicity in data exchange.
